P106 Towards mobile swollen joint count assessments

Abstract Background/Aims Rheumatoid arthritis (RA) requires regular monitoring, as treatment effectiveness can diminish over time. However, some people diagnosed with RA are unable to attend frequent hospital visits due to mobility limitations. We previously developed an AI-based system that measures finger joint thickness from standard photographs with 93.3% accuracy (MAE = 1.32 mm). This study focuses on the development of a mobile application prototype using this technology and its evaluation through patient and public involvement (PPI). Methods A prototype mobile application was developed to measure lateral thickness of finger joints. The application utilizes standard smartphone camera to capture hand images, automatically identifies joint positions, and calculates lateral thickness measurements in millimeters. The system operates without requiring camera calibration or specialized equipment, enabling accessible quantitative assessment of finger thickness in clinical or home settings. It also records prescription history, supports journaling and mood tracking to identify potential medication side effects, and enables communication with the rheumatology team. The prototype was presented to eight individuals with lived experience of RA during an online PPI meeting. A semi-structured discussion was conducted to explore usability, desired features, and requirements for clinical integration. The feedback was analysed to identify key development priorities of the proposed system and app design. Results Participants identified several key priorities for comprehensive disease monitoring. Participants emphasized the need for whole-body joint monitoring, extending beyond hands to all 28 commonly affected joints. Participants highlighted the importance of comprehensive symptom tracking, including journaling, mood monitoring, and fatigue monitoring using step-count data. Clinical integration was also a high priority, with strong requests for rheumatology teams to access patient-recorded finger swelling measurements, as well as summary reports of journal entries, mood tracking, and step-count trends before consultations. Additional recommendations included time-stamped entries to track temporal or seasonal patterns, as well as medication management features such as reminders and missed-dose alerts. Participants also emphasized the importance of recording hand stiffness duration and monitoring signs of inflammation. Conclusion This study demonstrates strong patient support for a mobile application that enables remote monitoring of RA. Participants prioritized detailed symptom tracking, integration with clinical care, and features that support self-management. The findings of this study will guide further development and clinical validation of the app, with the potential to enable remote monitoring of RA. Disclosure D. Eken: None. T. Neate: None. T. Abosi: None. N. Wilson: None. J. Galloway: None. L. Gionfrida: None.